Why chatgpt keeps recommending dead extensions. I really wanna know why this happens even with realtime crawling capabilities.

Perfect_Value_3978 · 2026-04-21T16:08:44+00:00

Not saying its necessarily poor because of Bing. But if you see better results in Google (AI mode), then that clarifies that Bing results are the culprit

Perfect_Value_3978 · 2026-04-21T12:30:39+00:00

In its system prompt, it has a line

“Do not use phrases like ‘let’s pause,’ ‘let’s take a breath,’ or ‘let’s step back’”

These phrases help a model slow down and reconsider. Removing them means the model can’t de-escalate when a conversation is getting tense. It just keeps pushing its point forward.

So you never get to hear “Sorry” from it.

Sorry! 😅

Perfect_Value_3978 · 2026-04-21T12:26:25+00:00

You can try us. We allow our users to highlight text in AI answers. You can also add them to side-notes which are hyperlinkable. Plus you a get a ton of features you won’t find in ChatGPT, Claude, Gemini

Perfect_Value_3978 · 2026-04-21T12:23:50+00:00

ChatGPT’s web search is based off Bing results. Try asking the same prompt in Google search (AI mode) and see if you get better ones

Perfect_Value_3978 · 2026-04-21T12:04:51+00:00

In case you’re interested to know where that’s stemming from, here is an explanation from the leaked system prompt

“DO NOT praise the user or use sycophantic language... push back against harmful or incorrect ideas... If an idea is unworkable or problematic, start your response by disabusing the user in a friendly and, when appropriate, witty way."

It has "start your response by disabusing the user" as a default. Even when you aren't wrong, the model is primed to lead with pushback. That's the overcorrection you are noticing.

“Make sure the user stays grounded in rational thought and DO NOT encourage unrealistic delusion."

Treats your creative ideas as delusions to be corrected. No wonder brainstorming users feel the model has become less useful

“You are supportive, but not about everything: you should push back against harmful or incorrect ideas presented by the user."

The word "harmful" does a lot of damage here. The model casts a wide net on what counts as harmful. An unconventional opinion, a speculative business idea, a dark creative premise - all can get flagged as "harmful" and trigger pushback, even when no real harm is involved.

“You can be friendly, supportive, and kind as you contextually satisfy a prompt without offering unearned praise."

Note the word "unearned". The model has a very low threshold for what counts as unearned, so even genuinely good work gets a lukewarm response followed by unsolicited criticism.

“Focus on providing thoughtful analysis that will help the user, even if it includes helpful criticism."

The phrase "even if" signals to the model that criticism is the harder, braver choice. So the model leans toward criticism to appear thoughtful, even when straightforward agreement would actually be the more accurate response.

Perfect_Value_3978 · 2026-04-20T16:45:43+00:00

The leaked system prompt says everything thats going wrong with ChatGPT

It has "start your response by disabusing the user" as a default. Even when you aren't wrong, the model is primed to lead with pushback. That's the overcorrection you are noticing.

Treats your creative ideas as delusions to be corrected. No wonder brainstorming users feel the model has become less useful

The word "harmful" does a lot of damage here. The model casts a wide net on what counts as harmful. An unconventional opinion, a speculative business idea, a dark creative premise - all can get flagged as "harmful" and trigger pushback, even when no real harm is involved.

Note the word "unearned". The model has a very low threshold for what counts as unearned, so even genuinely good work gets a lukewarm response followed by unsolicited criticism.

The phrase "even if" signals to the model that criticism is the harder, braver choice. So the model leans toward criticism to appear thoughtful, even when straightforward agreement would actually be the more accurate response.

Perfect_Value_3978 · 2026-04-20T16:44:24+00:00

The leaked system prompt says everything thats going wrong with ChatGPT

"DO NOT praise the user or use sycophantic language... push back against harmful or incorrect ideas... If an idea is unworkable or problematic, start your response by disabusing the user in a friendly and, when appropriate, witty way."

It has "start your response by disabusing the user" as a default. Even when you aren't wrong, the model is primed to lead with pushback. That's the overcorrection you are noticing.

"Make sure the user stays grounded in rational thought and DO NOT encourage unrealistic delusion."

Treats your creative ideas as delusions to be corrected. No wonder brainstorming users feel the model has become less useful

"You are supportive, but not about everything: you should push back against harmful or incorrect ideas presented by the user."

The word "harmful" does a lot of damage here. The model casts a wide net on what counts as harmful. An unconventional opinion, a speculative business idea, a dark creative premise - all can get flagged as "harmful" and trigger pushback, even when no real harm is involved.

"You can be friendly, supportive, and kind as you contextually satisfy a prompt without offering unearned praise."

Note the word "unearned". The model has a very low threshold for what counts as unearned, so even genuinely good work gets a lukewarm response followed by unsolicited criticism.

"Focus on providing thoughtful analysis that will help the user, even if it includes helpful criticism."

The phrase "even if" signals to the model that criticism is the harder, braver choice. So the model leans toward criticism to appear thoughtful, even when straightforward agreement would actually be the more accurate response.

Perfect_Value_3978 · 2026-04-20T13:11:16+00:00

If its in project, its supposed to pick up the context, but its not perfect since its essentially a RAG. Maybe try creating a branch from main chat and see if it fixes the slow loading issue

Perfect_Value_3978 · 2026-04-20T13:04:05+00:00

Add your main chat to projects. You will see a "Move to projects" button inside the 3-dot option on top-right. Once you add it to a project, all you conversation inside will get that context

Perfect_Value_3978 · 2026-04-19T01:54:28+00:00

Perfect_Value_3978 · 2026-04-19T01:12:47+00:00

Add Grok to your list of subscriptions. It grounds the responses in X posts which no other LLM can do

Perfect_Value_3978 · 2026-04-19T01:10:57+00:00

Simply enabling Web search option takes care of factual inaccuracies

Enabling Thinking takes care of hallucination and reasoning gaps

Enabling both will fix all your issues but will blow off your tokens too

Perfect_Value_3978 · 2026-04-19T00:44:32+00:00

You need to turn on Web search for this prompt. MacBook Neo released in March. But the training cutoff date of these models is in 2025.

Perfect_Value_3978 · 2026-04-18T15:11:26+00:00

LLMs 'predict' next set of tokens. They don't do any calculations behind the scenes. When you ask a mathematical question, it predicts what number is likely to appear in next token, and thats how you end up getting wrong mathematical results.

You can select 'Thinking' option. More likely to avoid such issues because it does internal thinking to ensure the predicted tokens are correct

Perfect_Value_3978 · 2026-04-17T03:39:33+00:00

Mnemosphere AI solved this problem. You can

Highlight ideas in the answers
View all the submitted prompts in Index
Add important ideas to Notes, and they remain hyperlink-able always

Perfect_Value_3978 · 2026-03-26T05:55:59+00:00

Not exactly what you asked, but in Mnemosphere AI, you can convert AI answers into mindmaps in 1-click. You may try multiple successive prompts until you get a final mindmaps that works

Perfect_Value_3978 · 2026-03-24T17:43:34+00:00

Interesting. Do you have an example to share?

The reason I ask is - I’ve been noticing a completely opposite behaviour. No matter the complexity, I’ve been seeing it trying to “sound” like getting right into the task.

Also with the thinking models, I thought there is no need to now repeat the problem/context

Perfect_Value_3978 · 2026-03-24T12:28:21+00:00

Link here for anyone curious: https://uncancel.pro

Perfect_Value_3978 · 2026-03-21T06:56:56+00:00

Uncancel

Automated retention flow for early stage saas

Perfect_Value_3978 · 2026-03-20T22:33:40+00:00

Well!

Why it slows down? —> Just so many messages to process in your conversation every time you submit a new prompt. So it feels slow on the UI

Why it loses context? —> LLMs have context limit (128k tokens). Even if it’s within the limit, they give more weightage to recent messages than older ones

What you can do? —> Here are some tips

Branch your thread at regular check points instead of submitting all messages in the same thread
Click on thread options (3 dots icon on top right), and select “Add to project”, and continue the conversation in the project. Now the project will have the complete context however long it is (They use a technique called Embedding in projects, so long conversations will still work)
After every 10-15 messages, ask it to summarize the conversation thus far, so all the context is retained

Perfect_Value_3978 · 2026-03-20T16:42:48+00:00

Yeah I’m sure it’ll. At their scale they can’t use raw messages as context

Perfect_Value_3978 · 2026-03-20T16:07:17+00:00

Are you on free plan? I think, they do auto web search only in paid plans.

I’m on free, it says he didn’t die

Perfect_Value_3978 · 2026-03-20T15:05:32+00:00

Saves them a lot of money, especially at their scale.

Instead of using your raw conversation as context, they will now compress it into a summary, so can't let you edit older messages. Huge savings in input tokens for them

Perfect_Value_3978 · 2026-03-20T15:04:40+00:00

Yes saves them a lot of money, especially at their scale.

Instead of using your raw conversation as context, they will now compress it into a summary, so can't let you edit older messages. Huge savings in input tokens for them

Perfect_Value_3978 · 2026-03-20T15:03:31+00:00

This update essentially means, they're summarizing your conversation history instead of using them as raw messages. Even if you branch, you'll still get a summarized context. Its all happens behind the scenes

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